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Proceedings of 2009 International Workshop on Information Security and Application (IWISA 2009)

Qingdao, China, November 21-22, 2009

Editors: Feng Gao and Xijun Zhu

AP Catalog Number: AP-PROC-CS-09CN004

ISBN: 978-952-5726-06-0

Page(s): 492-495

Multi-Urine Sediment Component Recognition Method

        Mei-li Shen

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Urine Sediment Component auto recognition system has important application to help doctor’s clinical diagnosis by digital image processing technology. Because Harr wavelet feature has good property of distinguish different components, the proposed method using AdaBoost to select a little part typical Harr feature which are taken as input data of SVM. The trained several bi-class SVM classifiers corresponding with different components are composed into a muti-class classifier. Moreover, in order to improve system speed, cascade accelerating algorithm is used. It is shown by experiment that the proposed method can not only effectively recognize different visible component of Urine sediment but also improve precision compared with other methods.

Index Terms

Urine Sediment recognition, SVM, AdaBoost, Multi-classification

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